4.7 Article

Statistical properties of supersonic turbulence in the Lagrangian and Eulerian frameworks

期刊

JOURNAL OF FLUID MECHANICS
卷 692, 期 -, 页码 183-206

出版社

CAMBRIDGE UNIV PRESS
DOI: 10.1017/jfm.2011.503

关键词

compressible turbulence; turbulence simulation; turbulence theory

资金

  1. International Max Planck Research School for Astronomy and Cosmic Physics (IMPRS-A)
  2. Heidelberg Graduate School of Fundamental Physics (HGSFP)
  3. Excellence Initiative of the German Research Foundation DFG [GSC 129/1]
  4. Baden-Wurttemberg-Stiftung [P-LS-SPII/18]
  5. German Bundesministerium fur Bildung und Forschung [05A09VHA]
  6. European Research Council under European Community [247060]
  7. Australian Research Council [DP110102191]
  8. Deutsche Forschungsgemeinschaft (DFG) [KL 1358/10, KL 1358/11, SFB 881]
  9. Heidelberg University
  10. German Excellence Initiative
  11. Leibniz Rechenzentrum [h0972, pr32lo]
  12. Forschungszentrum Julich [hhd20]
  13. ASC/Alliance Center for Astrophysical Thermonuclear Flashes at the University of Chicago

向作者/读者索取更多资源

We present a systematic study of the influence of different forcing types on the statistical properties of supersonic, isothermal turbulence in both the Lagrangian and Eulerian frameworks. We analyse a series of high-resolution, hydrodynamical grid simulations with Lagrangian tracer particles and examine the effects of solenoidal (divergence-free) and compressive (curl-free) forcing on structure functions, their scaling exponents, and the probability density functions of the gas density and velocity increments. Compressively driven simulations show significantly larger density contrast, more intermittent behaviour, and larger fractal dimension of the most dissipative structures at the same root mean square Mach number. We show that the absolute values of Lagrangian and Eulerian structure functions of all orders in the integral range are only a function of the root mean square Mach number, but independent of the forcing. With the assumption of a Gaussian distribution for the probability density function of the velocity increments for large scales, we derive a model that describes this behaviour.

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